Insight into molecular and chemical interactions and cellular phenotypes

Discoveries about disease processes

IPA is an all-in-one, web-based software application that enables analysis, integration, and understanding of data from gene expression, miRNA, and SNP microarrays, as well as metabolomics, proteomics, and RNAseq experiments. IPA can also be used for analysis of small-scale experiments that generate gene and chemical lists. IPA allows searches for targeted information on genes, proteins, chemicals, and drugs, and building of interactive models of experimental systems. Data analysis and search capabilities help in understanding the significance of data, specific targets, or candidate biomarkers in the context of larger biological or chemical systems. The software is backed by the Ingenuity Knowledge Base of highly structured, detail-rich biological and chemical findings.

For new academic users who have a limited amount of data to analyze. This Named User License has the full capabilities of Ingenuity Pathway Analysis for one year, but for a limited number of datasets.

The Ingenuity Pathway Analysis (IPA) is intended for molecular biology applications. This product is not intended for the diagnosis, prevention, or treatment of a disease.

Performance

A wealth of analysis capabilities in IPA

Causal Network Analysis

Causal Network Analysis comprehensively identifies upstream molecules that control the expression of the genes in datasets. Expanding beyond direct or single-hop relationships between the upstream regulator and the target molecules in the dataset, Causal Network Analysis uncovers networks of regulators that connect to the dataset targets. Focus on the networks that are of highest relevance by scoring the resulting causal networks against molecules, diseases, or functions of interest.

Comparison Analysis

Comparison Analysis provides quick visualization of canonical pathway score trends across dose, time, or other factors using the Comparison Analysis heat map. Prioritize by score, hierarchical cluster, or trend.

BioProfiler

A disease or phenotype can be rapidly profiled by understanding its associated genes and compounds. Identify genes known to be causally relevant as potential targets or identify targets of toxicity, associated known drugs, biomarkers, and pathways.

Upstream Regulator Analysis

This analysis predicts upstream molecules, including miRNA and transcription factors, that may be causing observed gene expression changes.

These analyses are used to determine the most significantly affected pathways.

Comparison Analysis

Comparison Analysis determines the most significant pathways, upstream regulators, diseases, biological functions, and more, across time points, dose, or other conditions.

Network Analysis

Build and explore transcriptional networks, miRNA–mRNA target networks, phosphorylation cascades, and protein–protein or protein–DNA interaction networks. Identify regulatory events that lead from signaling events to transcriptional effects. Understand toxicity responses by exploring connections between drugs or targets and related genes or chemicals. Edit and expand networks based on the molecular relationships most relevant to the project.

microRNA Target Filter

This filter reduces the number of steps it takes to confidently, quickly, and easily identify mRNA targets by allowing examination of miRNA–mRNA pairings, exploration of related biological context, and filtering based on relevant biological information as well as the expression information. The microRNA Target Filter provides insights into the biological effects of miRNAs, using experimentally validated interactions from TarBase and miRecords, as well as predicted miRNA–mRNA interactions from TargetScan. Additionally, Ingenuity IPA includes a large number of miRNA-related findings from the peer-reviewed literature.

Molecule Activity Predictor (MAP)

MAP enables interrogation of sub-networks and canonical pathways and hypothesis generation by selecting a molecule of interest, indicating up or down regulation, and simulating directional consequences of downstream molecules and the inferred activity upstream in the network or pathway.

Isoform View

Using Isoform view, the biological implications of high-throughput RNAseq data become clear. Significantly regulated isoforms in your experiment can be identified and their potential impact determined using information about functional protein domains and isoform-specific literature.

Gene and ChemView

Search and explore capabilities in Ingenuity IPA provide access to the most current findings on genes, drugs, chemicals, protein families, normal cellular and disease processes, and signaling and metabolic pathways.

Biomarker Filter

This filter rapidly identifies the best biomarker candidates based on biological characteristics most relevant to the discovery study.

Unparalled database knowledge

IPA leverages the Ingenuity Knowledge Base, a repository of expertly curated biological interactions and functional annotations created from millions of individually modeled relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases. These modeled relationships include rich details, links to the original article, and are reviewed for accuracy by Ph.D. scientists. The curated content in the Knowledge Base is structured into an ontology that allows for contextual information, computation by the applications, and synonym resolution to ensure consistency across concepts. These features make the Ingenuity Knowledge Base distinctive and unparalleled by any other database.